Object (e.g., face of an individual) recognition can be used to identify an object and/or individual from a 2-dimensional (2-D) digital image from a still camera and/or video camera based on characteristics that are unique to the object. Upon recognition, various systems can be provided to, for example, identify an individual and/or grant access to the individual. However, for a number of object recognition systems to identify an object in a 2-D image and/or accurately identify the object, the object may need to possess a particular pose (e.g., frontal pose, side pose) in the 2-D image. This, therefore, can present challenges when the object in the 2-D image does not possess the particular pose required by an object recognition system because the object recognition system may not be able to identify and/or accurately identify the object in the 2-D image.
Some prior solutions have utilized an eye detector to align a face of an individual to a normalized position (e.g., frontal pose) based upon a position of the eyes. Some of these solutions, however, can prove to be ineffective when a pose of the face of the individual varies by more than five degrees from a normalized position, for example. Other solutions have used methodology respecting a non-rigid deformation of face (e.g., facial expressions) to align the face of the individual. These solutions, however, can be computationally intensive, especially in regards to depth estimation of a face from a single 2-D image.